def test_ScalingModelObserver():
"""Test that the observer correctly logs data when passed a scaler."""
KB_dict = {
"__id__": "KB",
"is_scaled": True,
"scale": {
"n_parameters": 1,
"parameters": [0.5],
"est_standard_devs": [0.05],
"null_parameter_value": 1,
},
"configuration_parameters": {
"corrections": ["scale"]
},
}
KBmodel = KBScalingModel.from_dict(KB_dict)
experiment = Experiment()
experiment.scaling_model = KBmodel
experiment.identifier = "0"
scaler1 = mock.Mock()
scaler1.experiment = experiment
scaler1.active_scalers = None
observer = ScalingModelObserver()
observer.update(scaler1)
assert observer.data["0"] == KB_dict
msg = observer.return_model_error_summary()
assert msg != ""
mock_func = mock.Mock()
mock_func.return_value = {"plot": {"layout": {"title": ""}}}
with mock.patch("dials.algorithms.scaling.observers.plot_scaling_models",
new=mock_func):
observer.make_plots()
assert mock_func.call_count == 1
assert mock_func.call_args_list == [mock.call(KB_dict)]
experiment2 = Experiment()
experiment2.scaling_model = KBmodel
experiment2.identifier = "1"
scaler2 = mock.Mock()
scaler2.experiment = experiment2
scaler2.active_scalers = None
multiscaler = mock.Mock()
multiscaler.active_scalers = [scaler1, scaler2]
observer.data = {}
observer.update(multiscaler)
assert observer.data["0"] == KB_dict
assert observer.data["1"] == KB_dict
mock_func = mock.Mock()
mock_func.return_value = {"plot": {"layout": {"title": ""}}}
with mock.patch("dials.algorithms.scaling.observers.plot_scaling_models",
new=mock_func):
r = observer.make_plots()
assert mock_func.call_count == 2
assert mock_func.call_args_list == [
mock.call(KB_dict), mock.call(KB_dict)
]
assert all(i in r["scaling_model"] for i in ["plot_0", "plot_1"])
def test_KBScalingModel():
"""Test for the KB Scaling Model."""
# Test standard initialisation method.
configdict = {"corrections": ["scale", "decay"]}
parameters_dict = {
"scale": {
"parameters": flex.double([1.2]),
"parameter_esds": flex.double([0.1]),
},
"decay": {
"parameters": flex.double([0.01]),
"parameter_esds": flex.double([0.02]),
},
}
KBmodel = KBScalingModel(parameters_dict, configdict)
assert KBmodel.id_ == "KB"
assert "scale" in KBmodel.components
assert "decay" in KBmodel.components
assert list(KBmodel.components["scale"].parameters) == [1.2]
assert list(KBmodel.components["decay"].parameters) == [0.01]
assert list(KBmodel.components["scale"].parameter_esds) == [0.1]
assert list(KBmodel.components["decay"].parameter_esds) == [0.02]
# Test from_dict initialisation method.
KB_dict = {
"__id__": "KB",
"is_scaled": True,
"scale": {
"n_parameters": 1,
"parameters": [0.5],
"est_standard_devs": [0.05],
"null_parameter_value": 1,
},
"configuration_parameters": {
"corrections": ["scale"]
},
}
KBmodel = KBScalingModel.from_dict(KB_dict)
assert KBmodel.is_scaled is True
assert "scale" in KBmodel.components
assert "decay" not in KBmodel.components
assert list(KBmodel.components["scale"].parameters) == [0.5]
assert list(KBmodel.components["scale"].parameter_esds) == [0.05]
new_dict = KBmodel.to_dict()
assert new_dict == KB_dict
# Test again with all parameters
KB_dict = {
"__id__": "KB",
"is_scaled": True,
"scale": {
"n_parameters": 1,
"parameters": [0.5],
"est_standard_devs": [0.05],
"null_parameter_value": 1,
},
"decay": {
"n_parameters": 1,
"parameters": [0.2],
"est_standard_devs": [0.02],
"null_parameter_value": 0,
},
"configuration_parameters": {
"corrections": ["scale", "decay"]
},
}
KBmodel = KBScalingModel.from_dict(KB_dict)
assert KBmodel.is_scaled is True
assert "scale" in KBmodel.components
assert "decay" in KBmodel.components
assert list(KBmodel.components["scale"].parameters) == [0.5]
assert list(KBmodel.components["scale"].parameter_esds) == [0.05]
assert list(KBmodel.components["decay"].parameters) == [0.2]
assert list(KBmodel.components["decay"].parameter_esds) == [0.02]
new_dict = KBmodel.to_dict()
assert new_dict == KB_dict
with pytest.raises(RuntimeError):
KB_dict["__id__"] = "physical"
KBmodel = KBScalingModel.from_dict(KB_dict)
assert KBmodel.consecutive_refinement_order == [["scale", "decay"]]
assert "Decay component" in str(KBmodel)
def from_dict(d):
"""creates a scaling model from a dict"""
from dials.algorithms.scaling.model.model import KBScalingModel
return KBScalingModel.from_dict(d)